ArticleFrontiers in neuroinformatics2018
Unsupervised Manifold Learning Using High-Order Morphological Brain Networks Derived From T1-w MRI for Autism Diagnosis.
Article in Frontiers in neuroinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it, 76 citations in OpenAlex.
- Towards a brain-based predictome of mental illness.Human brain mapping · 2020Pooled it
- Improved deep canonical correlation fusion approach for detection of early mild cognitive impairment.Medical & biological engineering & computing · 2025Article
- A comprehensive survey of complex brain network representation.Meta-radiology · 2023Article
- Automatic autism spectrum disorder detection using artificial intelligence methods with MRI neuroimaging: A review.Frontiers in molecular neuroscience · 2022Review
- Machine learning for autism spectrum disorder diagnosis using structural magnetic resonance imaging: Promising but challenging.Frontiers in neuroinformatics · 2022Review
- Brain imaging-based machine learning in autism spectrum disorder: methods and applications.Journal of neuroscience methods · 2021Review
- Estimation of gender-specific connectional brain templates using joint multi-view cortical morphological network integration.Brain imaging and behavior · 2021Article
- Independent components of human brain morphology.NeuroImage · 2021Article
- Autism Spectrum Disorder Studies Using fMRI Data and Machine Learning: A Review.Frontiers in neuroscience · 2021Review
- A Novel Unit-Based Personalized Fingerprint Feature Selection Strategy for Dynamic Functional Connectivity Networks.Frontiers in neuroscience · 2021Article
- Large-Scale Brain Functional Network Integration for Discrimination of Autism Using a 3-D Deep Learning Model.Frontiers in human neuroscience · 2021Article
- Predicting full-scale and verbal intelligence scores from functional Connectomic data in individuals with autism Spectrum disorder.Brain imaging and behavior · 2020Article
- Gender differences in cortical morphological networks.Brain imaging and behavior · 2020Article
- Diagnosis of Autism Spectrum Disorder Using Central-Moment Features From Low- and High-Order Dynamic Resting-State Functional Connectivity Networks.Frontiers in neuroscience · 2020Article
- Morphological Brain Age Prediction using Multi-View Brain Networks Derived from Cortical Morphology in Healthy and Disordered Participants.Scientific reports · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain disorders, such as Autism Spectrum Disorder (ASD), alter brain functional (from fMRI) and structural (from diffusion MRI) connectivities at multiple levels and in varying degrees. While unraveling such alterations have been the focus of a large number of studies,
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.